INDUSTRY

COMPANY

GT Spectrum

Reports from the IT horizon

ALBUQUERQUE, N.M. -- A new "smart" machine that could fundamentally change how people interact with computers is being tested at the Department of Energy's Sandia National Laboratories.

For the past five years, a team led by Sandia cognitive psychologist Chris Forsythe has been developing cognitive machines that accurately infer user intent, remember experiences with users, and allow users to call on simulated experts to help them analyze situations and make decisions.

The initial goal of the work was to create a "synthetic human" -- a software program/computer that could think like a person.

"The benefits from this effort are expected to include augmenting human effectiveness and embedding these cognitive models into systems like robots and vehicles for better human-hardware interactions," said John Wagner, manager of Sandia's Computational Initiatives Department. "We expect to model, simulate and analyze humans and societies of humans for Department of Energy, military and national security applications."

Massive computers that could compute large amounts of data were available, said Forsythe. "But software that could realistically model how people think and make decisions was missing," he said.

There were two significant problems with previous modeling software. First, the software did not relate to how people actually make decisions -- it followed logical processes, which people don't necessarily do. People make decisions based, in part, on experiences and associative knowledge. Software models of human cognition also did not take into account factors such as emotions, stress and fatigue.

In an early project, Forsythe developed the framework for a computer program that used both factors.

Follow-up projects developed methodologies that allowed the knowledge of a specific expert to be captured in computer models and provided synthetic humans with episodic memory -- memory of experiences -- so they might apply their knowledge of specific experiences to solving problems in a manner that closely parallels what people do.

"Systems using this technology are tailored to a specific user, including the user's unique knowledge and understanding of the task," said Forsythe.

Work on cognitive machines started in 2002 with a contract from the Defense Advanced Research Projects Agency (DARPA) to develop a machine that can infer an operator's cognitive processes. This capability provides the potential for systems that augment the cognitive capacities of an operator through "discrepancy detection."

In discrepancy detection, the machine uses an operator's cognitive model to monitor its own state, detecting discrepancies between the machine's state and the operator's behavior.

Early this year, work began on Sandia's Next Generation Intelligent Systems Grand Challenge project.

"The goal of this Grand Challenge is to significantly improve the human capability to understand and solve national security problems, given the exponential growth of information and very complex environments," said Larry Ellis, the principal investigator.

"It's entirely possible," said Sandia's Forsythe, "that these cognitive machines could be incorporated into most computer systems produced within 10 years." -- Sandia National Laboratories

IBM Delivers World's Most Powerful Linux Supercomputer

TOKYO -- Japan's largest national research organization announced at the end of July that it ordered an IBM eServer Linux supercomputer that when completed, will deliver more than 11 trillion calculations per second, making it the world's most powerful Linux-based supercomputer.

It is expected to be more powerful than the Linux cluster at Lawrence Livermore National Laboratory in Livermore, Calif., which is currently ranked the third most powerful supercomputer in the world, according to the independent TOP500 List of Supercomputers.

The plan is to integrate the supercomputer with other non-Linux systems to form a massive, distributed computing grid -- enabling collaboration between corporations, academia and government -- to support various research including grid technologies, life sciences, bioinformatics and nanotechnology.